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Record W4365510635 · doi:10.1108/oxan-db278394

Canada faces the prospect of a public-sector strike

2023· article· en· W4365510635 on OpenAlexaboutno aff

Bibliographic record

VenueEmerald expert briefings · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsBlameGovernment (linguistics)NegotiationAgency (philosophy)RevenueAction (physics)Industrial actionBusinessGovernment revenuePublic administrationPolitical scienceLawFinanceSociologyPsychologySocial psychology

Abstract

fetched live from OpenAlex

Significance Employees at the Canada Revenue Agency voted for strike action last week, setting the scene for a potential showdown between the government and as many as 300,000 workers. Any strike action would be not only disruptive but politically divisive. Impacts With tax returns due on April 30, any disruption to their processing would delay government revenue collection. Strike action risks triggering public anger towards the unions, whose members are widely considered to be well rewarded. Conservatives will blame the governing Liberal party for any strikes while emphasising that they themselves would not negotiate. A prolonged disruption to non-critical government services has the potential to affect the Canadian economy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.900
Threshold uncertainty score0.728

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0330.005
Scholarly communication0.0130.002
Open science0.0020.002
Research integrity0.0190.010
Insufficient payload (model declined to judge)0.0200.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.043
GPT teacher head0.284
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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